Robust Confidence Intervals for PM2.5 Concentration Measurements in the Ecuadorian Park La Carolina [PDF]
Sensors, 2020 In this article, robust confidence intervals for PM2.5 (particles with size less than or equal to 2.5 μ m ) concentration measurements performed in La Carolina Park, Quito, Ecuador, have been built.
Wilmar Hernandez +3 more
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Robust Method for Confidence Interval Estimation in Outlier-Prone Datasets: Application to Molecular and Biophysical Data [PDF]
BiomoleculesEstimating confidence intervals in small or noisy datasets is a recurring challenge in biomolecular research, particularly when data contain outliers or exhibit high variability.
Victor V. Golovko
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Robust Confidence Intervals for Effect Size in the Two-Group Case [PDF]
, 2005 The probability coverage of intervals involving robust estimates of effect size based on seven procedures was compared for asymmetrically trimming data in an independent two-groups design, and a method that symmetrically trims the data.
H. J. Keselman +2 more
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Bootstrapping Confidence Intervals For Robust Measures Of Association [PDF]
, 2003 A Monte Carlo simulation study compared four bootstrapping procedures in generating confidence intervals for the robust Winsorized and percentage bend correlations.
Jason E. King
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ROCKET: Robust confidence intervals via Kendall’s tau for transelliptical graphical models [PDF]
Annals of Statistics, 2018 Undirected graphical models are used extensively in the biological and social sciences to encode a pattern of conditional independences between variables, where the absence of an edge between two nodes $a$ and $b$ indicates that the corresponding two ...
Rina Foygel Barber, Mladen Kolar
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Bootstrap Confidence Intervals for 11 Robust Correlations in the Presence of Outliers and Leverage Observations [PDF]
Methodology, 2022 Researchers often examine whether two continuous variables (X and Y) are linearly related. Pearson’s correlation (r) is a widely-employed statistic for assessing bivariate linearity.
Johnson Ching-Hong Li
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Robust Empirical Bayes Confidence Intervals [PDF]
Econometrica, 2020 We construct robust empirical Bayes confidence intervals (EBCIs) in a normal means problem. The intervals are centered at the usual linear empirical Bayes estimator, but use a critical value accounting for shrinkage. Parametric EBCIs that assume a normal
Timothy B. Armstrong +2 more
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Journal of Modern Applied Statistical Methods, 2020 In this paper, three robust confidence intervals are proposed as alternatives to the Student t confidence interval. The performance of these intervals was compared through a simulation study shows that Qn-t confidence interval performs the best and it is
Jennifer E. V. Lloyd +8 more
semanticscholar +5 more sources
Estimators of the multiple correlation coefficient: Local robustness and confidence intervals [PDF]
, 2003 Many robust regression estimators are defined by minimizing a measure of spread of the residuals. An accompanying R-2-measure, or multiple correlation coefficient, is then easily obtained.
Christophe Croux, Catherine Dehon
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Confidence intervals for robust estimates of measurement uncertainty [PDF]
Accreditation and Quality Assurance, 2020 Uncertainties arising at different stages of a measurement process can be estimated using analysis of variance (ANOVA) on duplicated measurements. In some cases, it is also desirable to calculate confidence intervals for these uncertainties.
Peter D. Rostron +2 more
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